Links between gut microbiome composition and fatty liver disease in a large population sample.
National Institute for Health and Welfare1, University of Turku2, Sahlgrenska University Hospital3, University of Helsinki4, University of Eastern Finland5, University of Amsterdam6, Baker IDI Heart and Diabetes Institute7, Monash University8, University of Melbourne9, University of California, San Diego10, University of Montana11, University of Cambridge12, Turku University Hospital13
TL;DR: The relationship between liver disease and the Gut Microbiome has been known for at least 80 years as mentioned in this paper, but this association remains mostly unstudied in the gene expression test.
Abstract: Fatty liver disease is the most common liver disease in the world. Its connection with the gut microbiome has been known for at least 80 y, but this association remains mostly unstudied in the gene...
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TL;DR: In this paper , the authors characterize genetic variations associated with microbial abundances in a single large-scale population-based cohort of 5,959 genotyped individuals with matched gut microbial metagenomes and dietary and health records (prevalent and follow-up).
Abstract: Human genetic variation affects the gut microbiota through a complex combination of environmental and host factors. Here we characterize genetic variations associated with microbial abundances in a single large-scale population-based cohort of 5,959 genotyped individuals with matched gut microbial metagenomes, and dietary and health records (prevalent and follow-up). We identified 567 independent SNP–taxon associations. Variants at the LCT locus associated with Bifidobacterium and other taxa, but they differed according to dairy intake. Furthermore, levels of Faecalicatena lactaris associated with ABO, and suggested preferential utilization of secreted blood antigens as energy source in the gut. Enterococcus faecalis levels associated with variants in the MED13L locus, which has been linked to colorectal cancer. Mendelian randomization analysis indicated a potential causal effect of Morganella on major depressive disorder, consistent with observational incident disease analysis. Overall, we identify and characterize the intricate nature of host–microbiota interactions and their association with disease. Genome-wide association analysis of gut microbial taxa in a single homogenous population-based cohort of 5,959 Finnish individuals identifies 567 independent SNP–taxon associations, including strong associations with LCT, ABO and MED13L.
105 citations
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TL;DR: A combination of genetics and dietary habits was shown to strongly shape the abundances of certain key bacterial members of the gut microbiota, and explain their genetic association, and this work identifies putative causal relationships between gut microbes and complex diseases using MR.
Abstract: Co-evolution between humans and the microbial communities colonizing them has resulted in an intimate assembly of thousands of microbial species mutualistically living on and in their body and impacting multiple aspects of host physiology and health. Several studies examining whether human genetic variation can affect gut microbiota suggest a complex combination of environmental and host factors. Here, we leverage a single large-scale population-based cohort of 5,959 genotyped individuals with matched gut microbial shotgun metagenomes, dietary information and health records up to 16 years post-sampling, to characterize human genetic variations associated with microbial abundances, and predict possible causal links with various diseases using Mendelian randomization (MR). Genome-wide association study (GWAS) identified 583 independent SNP-taxon associations at genome-wide significance (p
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TL;DR: In this article, a review of the current understanding of NAFLD pathogenesis and clarifies whether mitochondrial dysfunction and reactive nitrogen species (RNS) are culprits or bystanders of NASH progression.
Abstract: According to the 'multiple-hit' hypothesis, several factors can act simultaneously in nonalcoholic fatty liver disease (NAFLD) progression. Increased nitro-oxidative (nitroso-oxidative) stress may be considered one of the main contributors involved in the development and risk of NAFLD progression to nonalcoholic steatohepatitis (NASH) characterized by inflammation and fibrosis. Moreover, it has been repeatedly postulated that mitochondrial abnormalities are closely related to the development and progression of liver steatosis and NAFLD pathogenesis. However, it is difficult to determine with certainty whether mitochondrial dysfunction or oxidative stress are primary events or a simple consequence of NAFLD development. On the one hand, increasing lipid accumulation in hepatocytes could cause a wide range of effects from mild to severe mitochondrial damage with a negative impact on cell fate. This can start the cascade of events, including an increase of cellular reactive nitrogen species (RNS) and reactive oxygen species (ROS) production that promotes disease progression from simple steatosis to more severe NAFLD stages. On the other hand, progressing mitochondrial bioenergetic catastrophe and oxidative stress manifestation could be considered accompanying events in the vast spectrum of abnormalities observed during the transition from NAFL to NASH and cirrhosis. This review updates our current understanding of NAFLD pathogenesis and clarifies whether mitochondrial dysfunction and ROS/RNS are culprits or bystanders of NAFLD progression.
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TL;DR: In this paper , a review of the discovery of FXR as a bile acid sensor in the regulation of Bile acid metabolism and as a metabolic regulator of lipid, glucose, and energy homeostasis is presented.
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TL;DR: A nested case-control study to analyze longitudinal gut microbiota alterations in pregnant women with and without PE in the second and third trimesters of pregnancy found that the relative abundance of Bacteroidetes, Proteobacteria, and Enterobacteriaceae were significantly higher in the PE group than in the control group; and these differences were identified as taxonomic biomarkers of PE.
Abstract: BACKGROUND Preeclampsia (PE) is a serious complication that affects maternal and perinatal outcomes. However, the mechanisms have not been fully explained. This study was designed to analyze longitudinal gut microbiota alterations in pregnant women with and without PE in the second (T2) and third trimesters (T3). METHODS In this nested case-control study, which was conducted at Nanjing Maternity and Child Health Care Hospital, fecal samples from 25 PE patients (25 fecal samples obtained in T2 and 15 fecal samples obtained in T3) and 25 matched healthy controls (25 fecal samples obtained in T2 and 22 fecal samples obtained in T3) were collected, and the microbiota were analyzed using 16S rRNA gene sequencing. The diversity and composition of the microbiota of PE cases and controls were compared. RESULTS No significant differences in diversity were found between the PE and control groups (P > 0.05). In the control group, from T2 to T3, the relative abundances of Proteobacteria (median [Q1, Q3]: 2.25% [1.24%, 3.30%] vs. 0.64% [0.20%, 1.20%], Z = -3.880, P < 0.05), and Tenericutes (median [Q1, Q3]: 0.12% [0.03%, 3.10%] vs. 0.03% [0.02%, 0.17%], Z = -2.369, P < 0.05) decreased significantly. In the PE group, the relative abundance of Bacteroidetes in T2 was lower than in T3 (median [Q1, Q3]: 18.16% [12.99%, 30.46%] vs. 31.09% [19.89%, 46.06%], Z = -2.417, P < 0.05). In T2, the relative abundances of mircrobiota showed no significant differences between the PE group and the control group. However, in T3, the relative abundance of Firmicutes was significantly lower in the PE group than in the control group (mean ± standard deviation: 60.62% ± 15.17% vs. 75.57% ± 11.53%, t = -3.405, P < 0.05). The relative abundances of Bacteroidetes, Proteobacteria, and Enterobacteriaceae were significantly higher in the PE group than in the control group (median [Q1, Q3]: 31.09% [19.89%, 46.06%] vs. 18.24% [12.90%, 32.04%], Z = -2.537, P < 0.05; 1.52% [1.05%, 2.61%] vs. 0.64% [0.20%, 1.20%], Z = -3.310, P < 0.05; 0.75% [0.20%, 1.00%] vs. 0.01% [0.004%, 0.023%], Z = -4.152, P < 0.05). Linear discriminant analysis combined effect size measurements analysis showed that the relative abundances of the phylum Bacteroidetes, class Bacteroidia and order Bacteroidales were increased in the PE group, while those of the phylum Firmicutes, the class Clostridia, the order Clostridiales, and the genus unidentified Lachnospiraceae were decreased in the PE group; and these differences were identified as taxonomic biomarkers of PE in T3. CONCLUSION From T2 to T3, there was an obvious alteration in the gut microbiota. The gut microbiota of PE patients in T3 was significantly different from that of the control group.
27 citations
References
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TL;DR: Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
Abstract: As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
37,898 citations
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13 Aug 2016TL;DR: XGBoost as discussed by the authors proposes a sparsity-aware algorithm for sparse data and weighted quantile sketch for approximate tree learning to achieve state-of-the-art results on many machine learning challenges.
Abstract: Tree boosting is a highly effective and widely used machine learning method. In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges. We propose a novel sparsity-aware algorithm for sparse data and weighted quantile sketch for approximate tree learning. More importantly, we provide insights on cache access patterns, data compression and sharding to build a scalable tree boosting system. By combining these insights, XGBoost scales beyond billions of examples using far fewer resources than existing systems.
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TL;DR: The phyloseq project for R is a new open-source software package dedicated to the object-oriented representation and analysis of microbiome census data in R, which supports importing data from a variety of common formats, as well as many analysis techniques.
Abstract: Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
11,272 citations
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TL;DR: Prokka is introduced, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer, and produces standards-compliant output files for further analysis or viewing in genome browsers.
Abstract: UNLABELLED: The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers. AVAILABILITY AND IMPLEMENTATION: Prokka is implemented in Perl and is freely available under an open source GPLv2 license from http://vicbioinformatics.com/.
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TL;DR: As the global epidemic of obesity fuels metabolic conditions, the clinical and economic burden of NAFLD will become enormous, and random‐effects models were used to provide point estimates of prevalence, incidence, mortality and incidence rate ratios.
6,746 citations